High-fat diet feeding disrupts the coupling of thermoregulation to energy homeostasis.

OBJECTIVE: Preserving core body temperature across a wide range of ambient temperatures requires adaptive changes of thermogenesis that must be offset by corresponding changes of energy intake if body fat stores are also to be preserved. Among neurons implicated in the integration of thermoregulation with energy homeostasis are those that express both neuropeptide Y (NPY) and agouti-related protein (AgRP) (referred to herein as AgRP neurons). Specifically, cold-induced activation of AgRP neurons was recently shown to be required for cold exposure to increase food intake in mice. Here, we investigated how consuming a high-fat diet (HFD) impacts various adaptive responses to cold exposure as well as the responsiveness of AgRP neurons to cold. METHODS: To test this, we used immunohistochemistry, in vivo fiber photometry and indirect calorimetry for continuous measures of core temperature, energy expenditure, and energy intake in both chow- and HFD-fed mice housed at different ambient temperatures. RESULTS: We show that while both core temperature and the thermogenic response to cold are maintained normally in HFD-fed mice, the increase of energy intake needed to preserve body fat stores is blunted, resulting in weight loss. Using both immunohistochemistry and in vivo fiber photometry, we show that although cold-induced AgRP neuron activation is detected regardless of diet, the number of cold-responsive neurons appears to be blunted in HFD-fed mice. CONCLUSIONS: We conclude that HFD-feeding disrupts the integration of systems governing thermoregulation and energy homeostasis that protect body fat mass during cold exposure.

Identification of Hypothalamic Glucoregulatory Neurons That Sense and Respond to Changes in Glycemia.

To investigate whether glucoregulatory neurons in the hypothalamus can sense and respond to physiological variation in the blood glucose (BG) level, we combined continuous arterial glucose monitoring with continuous measures of the activity of a specific subset of neurons located in the hypothalamic ventromedial nucleus that express pituitary adenylate cyclase activating peptide (VMNPACAP neurons) obtained using fiber photometry. Data were collected in conscious, free-living mice during a 1-h baseline monitoring period and a subsequent 2-h intervention period during which the BG level was raised either by consuming a chow or a high-sucrose meal or by intraperitoneal glucose injection. Cross-correlation analysis revealed that, following a 60- to 90-s delay, interventions that raise the BG level reliably associate with reduced VMNPACAP neuron activity (P < 0.01). In addition, a strong positive correlation between BG and spontaneous VMNPACAP neuron activity was observed under basal conditions but with a much longer (∼25 min) temporal offset, consistent with published evidence that VMNPACAP neuron activation raises the BG level. Together, these findings are suggestive of a closed-loop system whereby VMNPACAP neuron activation increases the BG level; detection of a rising BG level, in turn, feeds back to inhibit these neurons. To our knowledge, these findings constitute the first evidence of a role in glucose homeostasis for glucoregulatory neurocircuits that, like pancreatic ß-cells, sense and respond to physiological variation in glycemia. ARTICLE HIGHLIGHTS: By combining continuous arterial glucose monitoring with fiber photometry, studies investigated whether neurons in the murine ventromedial nucleus that express pituitary adenylate cyclase activating peptide (VMNPACAP neurons) detect and respond to changes in glycemia in vivo. VMNPACAP neuron activity rapidly decreases (within <2 min) when the blood glucose level is raised by either food consumption or glucose administration. Spontaneous VMNPACAP neuron activity also correlates positively with glycemia, but with a longer temporal offset, consistent with reports that hyperglycemia is induced by experimental activation of these neurons. Like pancreatic ß-cells, neurons in the hypothalamic ventromedial nucleus appear to sense and respond to physiological variation in glycemia.

Cognition from the Body-Brain Partnership: Exaptation of Memory.

Examination of cognition has historically been approached from language and introspection. However, human language-dependent definitions ignore the evolutionary roots of brain mechanisms and constrain their study in experimental animals. We promote an alternative view, namely that cognition, including memory, can be explained by exaptation and expansion of the circuits and algorithms serving bodily functions. Regulation and protection of metabolic and energetic processes require time-evolving brain computations enabling the organism to prepare for altered future states. Exaptation of such circuits was likely exploited for exploration of the organism's niche. We illustrate that exploration gives rise to a cognitive map, and in turn, environment-disengaged computation allows for mental travel into the past (memory) and the future (planning). Such brain-body interactions not only occur during waking but also persist during sleep. These exaptation steps are illustrated by the dual, endocrine-homeostatic and memory, contributions of the hippocampal system, particularly during hippocampal sharp-wave ripples.

Action-driven remapping of hippocampal neuronal populations in jumping rats.

The current dominant view of the hippocampus is that it is a navigation "device" guided by environmental inputs. Yet, a critical aspect of navigation is a sequence of planned, coordinated actions. We examined the role of action in the neuronal organization of the hippocampus by training rats to jump a gap on a linear track. Recording local field potentials and ensembles of single units in the hippocampus, we found that jumping produced a stereotypic behavior associated with consistent electrophysiological patterns, including phase reset of theta oscillations, predictable global firing-rate changes, and population vector shifts of hippocampal neurons. A subset of neurons ("jump cells") were systematically affected by the gap but only in one direction of travel. Novel place fields emerged and others were either boosted or attenuated by jumping, yet the theta spike phase versus animal position relationship remained unaltered. Thus, jumping involves an action plan for the animal to traverse the same route as without jumping, which is faithfully tracked by hippocampal neuronal activity.

A metabolic function of the hippocampal sharp wave-ripple.

The hippocampus has previously been implicated in both cognitive and endocrine functions1-15. We simultaneously measured electrophysiological activity from the hippocampus and interstitial glucose concentrations in the body of freely behaving rats to identify an activity pattern that may link these disparate functions of the hippocampus. Here we report that clusters of sharp wave-ripples recorded from the hippocampus reliably predicted a decrease in peripheral glucose concentrations within about 10 min. This correlation was not dependent on circadian, ultradian or meal-triggered fluctuations, could be mimicked with optogenetically induced ripples in the hippocampus (but not in the parietal cortex) and was attenuated to chance levels by pharmacogenetically suppressing activity of the lateral septum, which is the major conduit between the hippocampus and the hypothalamus. Our findings demonstrate that a function of the sharp wave-ripple is to modulate peripheral glucose homeostasis, and offer a mechanism for the link between sleep disruption and blood glucose dysregulation in type 2 diabetes16-18.

On the methods for reactivation and replay analysis.

A major task in the history of neurophysiology has been to relate patterns of neural activity to ongoing external stimuli. More recently, this approach has branched out to relating current neural activity patterns to external stimuli or experiences that occurred in the past or future. Here, we aim to review the large body of methodological approaches used towards this goal, and to assess the assumptions each makes with reference to the statistics of neural data that are commonly observed. These methods primarily fall into two categories, those that quantify zero-lag relationships without examining temporal evolution, termed reactivation, and those that quantify the temporal structure of changing activity patterns, termed replay. However, no two studies use the exact same approach, which prevents an unbiased comparison between findings. These observations should instead be validated by multiple and, if possible, previously established tests. This will help the community to speak a common language and will eventually provide tools to study, more generally, the organization of neuronal patterns in the brain. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Variable specificity of memory trace reactivation during hippocampal sharp wave ripples.

Hippocampal sharp wave-ripples (SWR) are thought to mediate brain-wide reactivation of memory traces in service of memory consolidation. However, rather than the faithful replay of neural activity observed during a specific experience, reactivation in both the hippocampus and downstream regions is more variable. We suggest that variable reactivation is a unifying feature of recurrent brain circuits. In the hippocampus, self-organized activation during offline states is constrained by existing attractor manifolds, or maps, and may be biased toward particular mapped locations by salient experience, which results in the appearance of experience-specific replay. Similarly, the impact of SWR-associated reactivation on downstream regions is not a simple transfer of hippocampal representational content. Rather, the response of downstream regions depends on a transformation function, defined by both the feedforward and local circuit architecture, as well as the 'listening state' of the downstream region. We hypothesize that SWRs act as a multiplexed signal, the mnemonic specificity of which is largely determined by this transformation function, and discuss the implications of this framing for theories of systems consolidation.

Routing of Hippocampal Ripples to Subcortical Structures via the Lateral Septum.

The mnemonic functions of hippocampal sharp wave ripples (SPW-Rs) have been studied extensively. Because hippocampal outputs affect not only cortical but also subcortical targets, we examined the impact of SPW-Rs on the firing patterns of lateral septal (LS) neurons in behaving rats. A large fraction of SPW-Rs were temporally locked to high-frequency oscillations (HFOs) (120-180 Hz) in LS, with strongest coupling during non-rapid eye movement (NREM) sleep, followed by waking immobility. However, coherence and spike-local field potential (LFP) coupling between the two structures were low, suggesting that HFOs are generated locally within the LS GABAergic population. This hypothesis was supported by optogenetic induction of HFOs in LS. Spiking of LS neurons was largely independent of the sequential order of spiking in SPW-Rs but instead correlated with the magnitude of excitatory synchrony of the hippocampal output. Thus, LS is strongly activated by SPW-Rs and may convey hippocampal population events to its hypothalamic and brainstem targets.

Position-theta-phase model of hippocampal place cell activity applied to quantification of running speed modulation of firing rate.

Spiking activity of place cells in the hippocampus encodes the animal's position as it moves through an environment. Within a cell's place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position-theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time, and conditions; generates realistic place cell simulation data; and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields, we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.

Long-duration hippocampal sharp wave ripples improve memory.

Hippocampal sharp wave ripples (SPW-Rs) have been hypothesized as a mechanism for memory consolidation and action planning. The duration of ripples shows a skewed distribution with a minority of long-duration events. We discovered that long-duration ripples are increased in situations demanding memory in rats. Prolongation of spontaneously occurring ripples by optogenetic stimulation, but not randomly induced ripples, increased memory during maze learning. The neuronal content of randomly induced ripples was similar to short-duration spontaneous ripples and contained little spatial information. The spike content of the optogenetically prolonged ripples was biased by the ongoing, naturally initiated neuronal sequences. Prolonged ripples recruited new neurons that represented either arm of the maze. Long-duration hippocampal SPW-Rs replaying large parts of planned routes are critical for memory.

Space and Time: The Hippocampus as a Sequence Generator.

Neural computations are often compared to instrument-measured distance or duration, and such relationships are interpreted by a human observer. However, neural circuits do not depend on human-made instruments but perform computations relative to an internally defined rate-of-change. While neuronal correlations with external measures, such as distance or duration, can be observed in spike rates or other measures of neuronal activity, what matters for the brain is how such activity patterns are utilized by downstream neural observers. We suggest that hippocampal operations can be described by the sequential activity of neuronal assemblies and their internally defined rate of change without resorting to the concept of space or time.

Neurophysiological signatures of temporal coordination between retrosplenial cortex and the hippocampal formation.

Retrosplenial cortex (RSC) is heavily interconnected with a multitude of cortical regions and is directly connected with the hippocampal formation. As such, it is a likely coordinator of information transfer between the hippocampus (HPC) and cortex in the service of spatial cognition and episodic memory. The current work examined three potential temporal frameworks for retrosplenial-hippocampal communication, namely, theta frequency oscillations (6-12 Hz), sharp-wave/ripple events, and repeating, theta phase-locked shifts from low (30-65 Hz) to high (120-160 Hz) gamma frequency oscillations. From simultaneous recordings of single units and local field potentials (LFPs) in RSC and HPC, we report the presence of prominent theta, low-gamma, and high-gamma oscillations in the retrosplenial LFP. Retrosplenial and hippocampal theta rhythms were strongly coherent and subgroups of retrosplenial neurons exhibited either spiking at theta frequencies and/or spike-phase-locking to theta. Retrosplenial neurons were also phase-locked to local low- and high-gamma rhythms, and power in these frequency bands was coupled in a sequential fashion to specific phases of hippocampal and retrosplenial theta rhythms. Coordinated activity between the two regions also occurred during hippocampal sharp-wave/ripple events, where retrosplenial neuron populations were modulated in their spiking and retrosplenial LFPs exhibited sharp-wave-like events that co-occurred with those observed in HPC. These results identify several temporal windows of synchronization between RSC and HPC that may mediate cortico-hippocampal processes related to learning, memory, and spatial representation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Multiplexed oscillations and phase rate coding in the basal forebrain.

Complex behaviors demand temporal coordination among functionally distinct brain regions. The basal forebrain's afferent and efferent structure suggests a capacity for mediating this coordination at a large scale. During performance of a spatial orientation task, synaptic activity in this region was dominated by four amplitude-independent oscillations temporally organized by the phase of the slowest, a theta-frequency rhythm. Oscillation amplitudes were also organized by task epoch and positively correlated to the task-related modulation of individual neuron firing rates. For many neurons, spiking was temporally organized through phase precession against theta band field potential oscillations. Theta phase precession advanced in parallel to task progression, rather than absolute spatial location or time. Together, the findings reveal a process by which associative brain regions can integrate independent oscillatory inputs and transform them into sequence-specific, rate-coded outputs that are adaptive to the pace with which organisms interact with their environment.

Transformation of a Spatial Map across the Hippocampal-Lateral Septal Circuit.

The hippocampus constructs a map of the environment. How this "cognitive map" is utilized by other brain regions to guide behavior remains unexplored. To examine how neuronal firing patterns in the hippocampus are transmitted and transformed, we recorded neurons in its principal subcortical target, the lateral septum (LS). We observed that LS neurons carry reliable spatial information in the phase of action potentials, relative to hippocampal theta oscillations, while the firing rates of LS neurons remained uninformative. Furthermore, this spatial phase code had an anatomical microstructure within the LS and was bound to the hippocampal spatial code by synchronous gamma frequency cell assemblies. Using a data-driven model, we show that rate-independent spatial tuning arises through the dynamic weighting of CA1 and CA3 cell assemblies. Our findings demonstrate that transformation of the hippocampal spatial map depends on higher-order theta-dependent neuronal sequences. VIDEO ABSTRACT.

Cell assemblies of the basal forebrain.

The basal forebrain comprises several heterogeneous neuronal subgroupings having modular projection patterns to discrete sets of cortical subregions. Each cortical region forms recurrent projections, via prefrontal cortex, that reach the specific basal forebrain subgroups from which they receive afferents. This architecture enables the basal forebrain to selectively modulate cortical responsiveness according to current processing demands. Theoretically, optimal functioning of this distributed network would be enhanced by temporal coordination among coactive basal forebrain neurons, or the emergence of "cell assemblies." The present work demonstrates assembly formation in rat basal forebrain neuronal populations during a selective attention task. Neuron pairs exhibited coactivation patterns organized within beta-frequency time windows (55 ms), regardless of their membership within distinct bursting versus nonbursting basal forebrain subpopulations. Thus, the results reveal a specific temporal framework for integration of information within basal forebrain networks and for the modulation of cortical responsiveness.

Task-phase-specific dynamics of basal forebrain neuronal ensembles.

Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases.